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This Startup’s AI Found Critical Vulnerabilities That Anthropic’s Mythos Missed Startup Depthfirst claims its AI found some major flaws in tools that help run much of the internet, all for a tenth of the cost of Anthropic’s comparable model Mythos.

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🚨 ANTHROPIC JUST REVEALED CLAUDE MYTHOS ABILITIES Anthropic just formally announced "Claude Mythos Preview" and launched "Project Glasswing" to deploy it for cybersecurity defense. The models are unlocking completely new, autonomous behaviors. This isn't about slightly better benchmark scores. This is about what the model can do. Here are the direct quotes from Anthropic’s research team (including Dario) on exactly what Mythos is capable of: • Chaining Exploits: "It has the ability to chain together vulnerabilities... this model is able to create exploits out of three, four, sometimes five vulnerabilities that in sequence give you some kind of very sophisticated end outcome." • The Professional Standard: "The model that we're experimenting with is, by and large, as good as a professional human at identifying bugs." • Unprecedented Autonomy: "It's just generally better at pursuing really long-range tasks that are kind of like the tasks that a human security researcher would do throughout the course of an entire day." The Reality Check: Dario Amodei flat out said: "There's a kind of accelerating exponential... Claude Mythos Preview is a particularly big jump along that point." Because this model has become so capable at identifying zero-days, they are restricting its release to top tech partners to try to patch the world's software before these capabilities leak out. The autonomous researcher era has officially arrived. It’s over 💀

Chris

46,077 Aufrufe • vor 2 Monaten

The Federal Reserve and the US Treasury just summoned Wall Street's most powerful CEOs to an emergency meeting. The reason: An AI model so dangerous they couldn't discuss it over the phone. This is the FIRST time the Treasury Secretary and Fed Chair jointly called bank CEOs into a room since October 13, 2008. That day, Paulson and Bernanke unveiled the $250 billion TARP bailout to stop the entire financial system from collapsing. This time it wasn't about banks failing. It was about an AI that can hack EVERY major operating system and web browser on earth. Here's what this means: Anthropic built a new AI model called Mythos. During internal testing, it found THOUSANDS of zero-day vulnerabilities across every major operating system and every major web browser on earth. Including a 27yo bug in OpenBSD, an operating system literally famous for being unhackable. And several vulnerabilities in the Linux kernel that could give an attacker complete control of any machine running it. Nobody asked it to do this. The capabilities were NOT trained. They literally just emerged as the model got smarter at coding and reasoning. Anthropic's researchers said they found more bugs in a few weeks with Mythos than they had found in their entire careers combined. On Tuesday, Bessent and Powell pulled the CEOs of Citi, Morgan Stanley, Bank of America, Wells Fargo, and Goldman Sachs into Treasury headquarters. The message: This AI exists, similar ones are coming, your banks need to be ready. But JPMorgan's Jamie Dimon didn't show up. Here's why that matters more than you think: JPMorgan is the ONLY bank that already has access to the model. They're one of 12 founding partners in Anthropic's "Project Glasswing" which gives select companies early access to Mythos to find and fix their own vulnerabilities before hackers get similar tools. So 5 bank CEOs managing $9 TRILLION in assets got called into a room to be warned about a threat. The one bank with the actual tools to defend against it? Their CEO skipped the meeting. The same day JPMorgan analysts issued buy ratings on CrowdStrike and Palo Alto Networks, citing Glasswing as the catalyst. One side of Wall Street got the warning. The other got the weapon AND the trading thesis. But here's the thing... The same AI that finds and fixes vulnerabilities can also EXPLOIT them. Anthropic admitted it directly. Mythos "can surpass all but the most skilled humans at finding and exploiting software vulnerabilities." In one test, it wrote a browser exploit chaining FOUR separate vulnerabilities, escaping both the renderer sandbox and the OS sandbox. Fully autonomous. Zero human involvement. Over 99% of the vulnerabilities it found haven't been patched yet. Meanwhile, Anthropic is fighting the Pentagon in court. The Defense Department labeled them a "supply-chain risk" after they refused to let their AI be used for autonomous targeting of US citizens. A San Francisco judge blocked the designation, calling the Pentagon's actions "disturbing." Then a DC appeals court reversed that protection. On the same day as the emergency bank meeting. One branch of government is treating Anthropic as a national security threat. Another is begging Wall Street to prepare for its technology. And the intelligence community is quietly asking how to use Mythos offensively against adversaries. The last time this many powerful people were this nervous about a single technology was nuclear weapons. But the difference is that Nukes required a government, billions of dollars, and uranium enrichment facilities. This just required a better AI model.

Ricardo

41,668 Aufrufe • vor 2 Monaten

Anthropic admitted they built an AI so capable they were scared to release it and the number that explains why is 250. Anthropic's CFO Krishna Rao described in this clip what happened when they ran Mythos against an open source codebase that a previous frontier model had already analyzed. The prior model found 22 security vulnerabilities, Mythos found 250. In the same codebase, that the previous model had already reviewed and flagged as relatively clean. That number, more than 11 times as many vulnerabilities discovered is not just a benchmark improvement, it is a signal that there is an entire layer of software infrastructure that humanity has been operating under the assumption was secure and that assumption may no longer hold. The UK AI Security Institute independently evaluated Mythos Preview and confirmed what the internal numbers suggested. On expert level capture the flag challenges that no model could complete before April 2025, Mythos succeeded 73% of the time and it became the first model ever to complete a complex end-to-end attack range from start to finish, autonomously, without human guidance. The World Economic Forum called this a new security-driven era for AI, the Governor of the Bank of England publicly warned that Anthropic may have found a way to unlock the entire cyber-risk landscape, and the European Central Bank began quietly contacting financial institutions to assess their security posture. The response from Anthropic is what makes this story genuinely important. Rather than shelving the model or publishing it as a standard API release, Rao described a phased approach restricting access to a controlled group, focusing specifically on how the cyber capabilities can be used defensively rather than offensively and treating that framework as a template for how to release powerful but dangerous models in the future. The broader context makes that framing even more significant. AI generated code is already creating ten times more security vulnerabilities than human-written code, 63% of organizations reported experiencing an AI driven cyberattack in the past 12 months, and traditional signature-based security tools were built for a threat model that no longer describes the attack surface companies are defending against. Mythos represents a genuine leap in what autonomous security reasoning can do and it cuts both ways. The model that can find 250 vulnerabilities in a codebase a prior model rated as mostly clean is also, in the wrong hands, the model that can exploit those 250 vulnerabilities before a human defender has even finished reading the report. Anthropic's phased release strategy is not just a legal or PR decision, it is the most honest signal yet from a frontier lab that safety governance and capability development can no longer be treated as separate workstreams. The question is not whether this technology gets deployed, it is whether the institutions using it defensively stay ahead of the ones who will eventually use it offensively and whether the labs building it can keep those two timelines from inverting.

Milk Road AI

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